Journal of Marine Science and Application

, Volume 1, Issue 2, pp 12–17 | Cite as

Distributed and redundant design of ship monitoring and control network

  • Zhang Jun-dong 
  • Sui Jiang-hua 


The world trend in ship automation is to integrate the monitoring, intelligent control and systematic management of the instruments and equipments both on bridge and in engine room. The paper presents a design scheme of the ship integrated monitoring and operating system based on two layers distributed and redundant computer network. The lower layer network is the field bus network connected mainly by CAN bus; the upper one is the PC local network in TCP/IP protocol, which consisted of a database server, monitoring and operating computers, industrial computers and a set of switches. Distributed schemes are fully applied to both software and hardware. This paper specifically describes the composition, software distribution and redundant technology of the upper local network and gives some important sample codes for the implement of the redundant and distributed design. The technologies here have been proved in the many applications and it may be applied to other industrial fields.

Key words

Ship monitoring and operating Network Distribution Redundancy 

CLC number


Document code


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    WU XIAOYUN, CAO ZHONGSHEN. System structure and function description of CAN field bus control and monitor system for automation of engine room on ships [J]. Shipbuilding of China, 2001, 42(1): 69–74 (in Chinese).MathSciNetGoogle Scholar
  2. [2]
    LIN YEJIN, ZHU SHAOLU. Software design on engine room intelligent monitoring system [J]. Journal of Dalian Maritime University, 1988, 24 (4): 52–55 (in Chinese).Google Scholar

Copyright information

© Harbin Engineering University 2002

Authors and Affiliations

  • Zhang Jun-dong 
    • 1
  • Sui Jiang-hua 
    • 1
  1. 1.Marine Engineering CollegeDalian Maritime UniversityDalianChina

Personalised recommendations